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<p>Declaration of the <code>Node</code> class and various derived node classes for neural network operations.  
<a href="#details">More...</a></p>
<div class="textblock"><code>#include &lt;memory&gt;</code><br />
<code>#include &quot;<a class="el" href="_tensor_8cuh_source.html">Tensor.cuh</a>&quot;</code><br />
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<p><a href="_nodes_8cuh_source.html">Go to the source code of this file.</a></p>
<table class="memberdecls">
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Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1_node.html">nz::nodes::Node</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Base class for nodes in a neural network or computational graph.  <a href="classnz_1_1nodes_1_1_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1io_1_1_input_node.html">nz::nodes::io::InputNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents an input node in a computational graph.  <a href="classnz_1_1nodes_1_1io_1_1_input_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1io_1_1_output_node.html">nz::nodes::io::OutputNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Base class for loss function nodes in a computational graph.  <a href="classnz_1_1nodes_1_1io_1_1_output_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_add_node.html">nz::nodes::calc::AddNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a node that performs element-wise addition between two input tensors.  <a href="classnz_1_1nodes_1_1calc_1_1_add_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_mat_mul_node.html">nz::nodes::calc::MatMulNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a matrix multiplication operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_mat_mul_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_scalar_mul_node.html">nz::nodes::calc::ScalarMulNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar multiplication operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_scalar_mul_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_scalar_div_node.html">nz::nodes::calc::ScalarDivNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar division operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_scalar_div_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_scalar_add_node.html">nz::nodes::calc::ScalarAddNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar addition operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_scalar_add_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_scalar_sub_node.html">nz::nodes::calc::ScalarSubNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a scalar subtraction operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_scalar_sub_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_sub_node.html">nz::nodes::calc::SubNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a subtraction operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_sub_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_re_l_u_node.html">nz::nodes::calc::ReLUNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Rectified Linear Unit (ReLU) operation node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_re_l_u_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_sigmoid_node.html">nz::nodes::calc::SigmoidNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Sigmoid activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_sigmoid_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_tanh_node.html">nz::nodes::calc::TanhNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a hyperbolic tangent (tanh) activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_tanh_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_leaky_re_l_u_node.html">nz::nodes::calc::LeakyReLUNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Leaky Rectified Linear Unit (LeakyReLU) activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_leaky_re_l_u_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_swish_node.html">nz::nodes::calc::SwishNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Swish activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_swish_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_e_l_u_node.html">nz::nodes::calc::ELUNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents an Exponential Linear Unit (ELU) activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_e_l_u_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_hard_sigmoid_node.html">nz::nodes::calc::HardSigmoidNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Hard Sigmoid activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_hard_sigmoid_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_hard_swish_node.html">nz::nodes::calc::HardSwishNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents a Hard Swish activation function node in a computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_hard_swish_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_softmax_node.html">nz::nodes::calc::SoftmaxNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implements the Softmax activation function as a node in a neural network computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_softmax_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_reshape_node.html">nz::nodes::calc::ReshapeNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implements tensor shape transformation within a neural network computational graph.  <a href="classnz_1_1nodes_1_1calc_1_1_reshape_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_expand_node.html">nz::nodes::calc::ExpandNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Expands tensors with batch size 1 to arbitrary batch dimensions through data replication.  <a href="classnz_1_1nodes_1_1calc_1_1_expand_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_img2_col_node.html">nz::nodes::calc::Img2ColNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implements im2col transformation for efficient convolution operations in neural networks.  <a href="classnz_1_1nodes_1_1calc_1_1_img2_col_node.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_col2_img_node.html">nz::nodes::calc::Col2ImgNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Reconstructs spatial tensors from column matrices generated by im2col transformation.  <a href="classnz_1_1nodes_1_1calc_1_1_col2_img_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_average_pooling_node.html">nz::nodes::calc::AveragePoolingNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implements average pooling operation for spatial downsampling in neural networks.  <a href="classnz_1_1nodes_1_1calc_1_1_average_pooling_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_global_avg_pool_node.html">nz::nodes::calc::GlobalAvgPoolNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Performs global average pooling operation across spatial dimensions of input tensor.  <a href="classnz_1_1nodes_1_1calc_1_1_global_avg_pool_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_max_pooling_node.html">nz::nodes::calc::MaxPoolingNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Implements max pooling operation for spatial downsampling with feature preservation.  <a href="classnz_1_1nodes_1_1calc_1_1_max_pooling_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1calc_1_1_global_max_pool_node.html">nz::nodes::calc::GlobalMaxPoolNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Performs global max pooling operation across spatial dimensions of input tensor.  <a href="classnz_1_1nodes_1_1calc_1_1_global_max_pool_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1loss_1_1_mean_squared_error_node.html">nz::nodes::loss::MeanSquaredErrorNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents the Mean Squared Error (MSE) loss function node in a computational graph.  <a href="classnz_1_1nodes_1_1loss_1_1_mean_squared_error_node.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classnz_1_1nodes_1_1loss_1_1_binary_cross_entropy_node.html">nz::nodes::loss::BinaryCrossEntropyNode</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight">Represents the Binary Cross-Entropy (BCE) loss function node in a computational graph.  <a href="classnz_1_1nodes_1_1loss_1_1_binary_cross_entropy_node.html#details">More...</a><br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="namespaces" name="namespaces"></a>
Namespaces</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">namespace &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacenz_1_1nodes.html">nz::nodes</a></td></tr>
<tr class="memdesc:namespacenz_1_1nodes"><td class="mdescLeft">&#160;</td><td class="mdescRight">Contains classes and functionality for nodes in a neural network or computational graph. <br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">namespace &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacenz_1_1nodes_1_1io.html">nz::nodes::io</a></td></tr>
<tr class="memdesc:namespacenz_1_1nodes_1_1io"><td class="mdescLeft">&#160;</td><td class="mdescRight">This namespace contains standard nodes used in computational graphs for neural networks. <br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">namespace &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacenz_1_1nodes_1_1calc.html">nz::nodes::calc</a></td></tr>
<tr class="memdesc:namespacenz_1_1nodes_1_1calc"><td class="mdescLeft">&#160;</td><td class="mdescRight">Contains classes and functionality for computation nodes in a neural network or computational graph. <br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">namespace &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="namespacenz_1_1nodes_1_1loss.html">nz::nodes::loss</a></td></tr>
<tr class="memdesc:namespacenz_1_1nodes_1_1loss"><td class="mdescLeft">&#160;</td><td class="mdescRight">Contains loss function nodes for computing various loss metrics in a machine learning model. <br /></td></tr>
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</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a id="func-members" name="func-members"></a>
Functions</h2></td></tr>
<tr class="memitem:a42672c2d7708ae1d0c071fd9bef6c03c" id="r_a42672c2d7708ae1d0c071fd9bef6c03c"><td class="memTemplParams" colspan="2">template&lt;typename T &gt; </td></tr>
<tr class="memitem:a42672c2d7708ae1d0c071fd9bef6c03c"><td class="memTemplItemLeft" align="right" valign="top">std::enable_if_t&lt; std::is_base_of_v&lt; <a class="el" href="classnz_1_1nodes_1_1_node.html">Node</a>, T &gt;, std::ostream &amp; &gt;&#160;</td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacenz_1_1nodes.html#a42672c2d7708ae1d0c071fd9bef6c03c">nz::nodes::operator&lt;&lt;</a> (std::ostream &amp;os, const T &amp;node)</td></tr>
<tr class="memdesc:a42672c2d7708ae1d0c071fd9bef6c03c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Overloads the <code>&lt;&lt;</code> operator to print information about a node.  <br /></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Declaration of the <code>Node</code> class and various derived node classes for neural network operations. </p>
<p>This file provides the declaration of the <code>Node</code> class, which serves as an abstract base class for nodes in a neural network or computational graph. It also defines a variety of derived node classes that represent specific layers or operations commonly used in machine learning models, such as activation functions, loss functions, and mathematical operations.</p>
<p>The <code>Node</code> class encapsulates the following key features:</p><ul>
<li><b>Forward and Backward Passes</b>: Defines pure virtual functions <code>forward()</code> and <code>backward()</code>, which must be implemented by derived classes to define the specific operations for data propagation and gradient computation.</li>
<li><b>Tensor Operations</b>: Interacts with <code>Tensor</code> objects for storing and manipulating data.</li>
<li><b>Graph Structure</b>: Each node has input and output connections, represented by vectors of pointers to other nodes and shared pointers to tensors, respectively.</li>
</ul>
<p>The file also defines several derived classes for specific operations, such as:</p><ul>
<li><b>Activation Functions</b>: <code>LeakyReLUNode</code>, <code>SwishNode</code>, <code>ELUNode</code>, <code>HardSigmoidNode</code>, <code>HardSwishNode</code>, and <code>SoftmaxNode</code>.</li>
<li><b>Mathematical Operations</b>: <code>AddNode</code>, <code>MatMulNode</code>, <code>ScalarMulNode</code>, <code>ScalarDivNode</code>, etc.</li>
<li><b>Loss Functions</b>: <code>MeanSquaredErrorNode</code>, <code>BinaryCrossEntropyNode</code>, which are used for computing the error during training.</li>
</ul>
<p>These classes implement the <code>forward()</code> and <code>backward()</code> methods to perform specific operations and propagate gradients during the training process of the neural network.</p>
<p>This class is part of the <code><a class="el" href="namespacenz_1_1nodes.html" title="Contains classes and functionality for nodes in a neural network or computational graph.">nz::nodes</a></code> namespace, and each derived class represents a specific computational layer or operation used in deep learning models.</p>
<dl class="section note"><dt>Note</dt><dd><ul>
<li>Ensure that proper memory management is applied when using these node classes, particularly when dealing with GPU memory and tensor data.</li>
</ul>
</dd></dl>
<dl class="section author"><dt>Author</dt><dd>Mgepahmge (<a href="https://github.com/Mgepahmge">https://github.com/Mgepahmge</a>)</dd></dl>
<dl class="section date"><dt>Date</dt><dd>2024/11/29 </dd></dl>

<p class="definition">Definition in file <a class="el" href="_nodes_8cuh_source.html">Nodes.cuh</a>.</p>
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